Constant technological change creates opportunity but a tough environment for both organizations and employees – as Bob Dylan/Timothee Chalamet would say, ‘the times they are a’changin’. Many companies are dealing with their own complete unknown. To survive and thrive in this era of uncertainty, firms are constantly striving to make their operations more efficient and become more productive. To do so, they need to understand the skills landscape in their organization. This will allow for greater resilience and agility, and ultimately make their business more competitive.
But current efforts to understand skills are inadequate. Skills matrices, for example, are usually out of date very quickly after they are created. It’s difficult to ascertain how ‘fresh’ an employee skillset is, meaning there is always a risk of asking someone to work on a task they aren’t really able to do and therefore difficult to effectively lend and borrow resources across teams. It’s also challenging to get a departmental or organizational view of skills, or to understand how many people have particular types of skills in your organization. Without that insight, organizations can’t effectively achieve their goals.
In this blog, we’re suggesting four ways that organizations like yours can get the lay of their skills landscape, and turn that into actionable insight. Organizations striving to be competitive need proactive strategies to bridge skills gaps and future-proof their workforce. Here are four ways organizations can use a Skills Center to keep ahead of their skills gap:
1: Use AI to be dynamic
Since traditional skills matrices often fall into disuse due to challenges around manual upkeep, it makes sense to use AI to do that upkeep. By continuously analyzing work data, an AI can identify what skills everyone in your operation has meaning that you can stop relying on outdated information and the gut feel your managers have, in favor of hard data .
You could even categorize the freshness of a person’s skill based on performance over the last 90 days, for example. This provides a snapshot of team strengths and areas for development, enabling better task allocation and strategic planning– be this data analytics for risk assessment and fraud detection, cybersecurity, or customer insights.
2: Make it measurable
Rating the freshness of people’s skills is one way of making the skills in your organization more measurable, but you can go further. Understanding how long it takes employees to master specific skills is vital for workforce planning, especially if you’re planning to lend and borrow resource across teams. And while someone is learning, how productive are they likely to be?
If you have AI gathering skills data based on work completed, it’s a relatively short step to cross-reference that with work history to uncover the learning curves for different tasks in your operation. Data might show that an underwriter, for example, typically needs six months to become fully proficient – which could be better or worse than your managers had assumed. Perhaps banking employees are getting up to speed on ESG and sustainable finance quicker than you expected.
Monitoring learning curves allows firms to:
- Accurately plan onboarding and upskilling programs
- Identify employees who are taking longer to become proficient at something and provide targeted support
- Ensure operational continuity by aligning training timelines with business demands.
3: Marry it all up
Skills gaps can emerge where and when you least expect them. They can also widen rapidly, particularly in industries undergoing technological or regulatory change. But firms can mitigate some of this by marrying their skills catalogue with forward planning tools to identify future work that they need more skilled employees to fill. Again, AI is an indispensable tool for identifying discrepancies between current workforce skills and future business needs.
If you can build this capability into your operations, you will be able to:
- Pinpoint critical areas requiring upskilling
- Align training initiatives with long-term-strategic goals
- Avoid last-minute scrambles to fill skill shortages during peak demand periods and reduce the cost of outsourcing.
For example, this might mean identifying a shortage of employees skilled in handling aviation claims and implementing targeted training programs to address the gap before it impacts service delivery. Or, during a seasonal surge in customer service requests, the system can identify employees with the relevant skills and capacity to handle the increased workload. If you know compliance changes are on the horizon, anti-money laundering regulations for example, AI can help you build a roadmap to ensure you are ready.
4: Make it relevant
Evaluating individual skills in isolation may only get you so far, so quickly. Grouping them by roles and processes provides a broader view of your organization’s capabilities and ensures critical functions have adequate coverage. AI can help managers to assess team competencies across aggregated roles like underwriting or claims adjustment – and ensure that the everyone’s view of skills, from team members to the C-suite, is in real time. Rolling everything up to give a complete view of skills ensures leaders don’t miss anything. An employee might be great at adjusting claims but if they don’t possess the required qualifications, the California Fair Claims Practices Regulations for example, they may be unable to work on a certain project.
In summary, this allows firms to:
- Ensure regulatory compliance by verifying that qualified employees handle specialized tasks
- Highlight potential risks in processes that depend on specific skill sets
- Improve resource allocation by matching employees with tasks that align with their capabilities
Leverage AI for real-time adaptability
By creating dynamic skills matrices, measuring learning curves, marrying skills matrices with forward planning, and ensuring relevancy, businesses can build a resilient, future-ready workforce. At ActiveOps, we’re proud to have launched Skills Center, helping ops leaders do all those things and more.
An automatically refreshing skills catalogue, Skills Center takes individual performance of a particular task, automatically assesses completion of it over last 90 days and gives a skill level. You can also manually add soft skills including management, mental health first aid certifications, and more to create a complete picture.
The ActiveOps Skills Center, part of ControliQ Series 4, uses AI-powered Decision Intelligence to ensure that teams are ready to tackle the challenges of today and tomorrow. Book a demo to see the Skills Center action.
Smart skills is 98% quicker than the manual process we have in place currently.
Getting ahead of your skills gap is all about proactive, data-driven strategy. By creating dynamic skills matrices, tracking learning curves, and leveraging AI for adaptability, businesses can build a resilient, future-ready workforce.
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